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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<!-- Meta tags for social media banners, these should be filled in appropriatly as they are your "business card" -->
<!-- Replace the content tag with appropriate information -->
<meta name="description" content="DESCRIPTION META TAG">
<meta property="og:title" content="LBSTER"/>
<meta property="og:description" content="LBSTER"/>
<meta property="og:url" content="URL OF THE WEBSITE"/>
<!-- Path to banner image, should be in the path listed below. Optimal dimenssions are 1200X630-->
<meta property="og:image" content="static/image/your_banner_image.png" />
<meta property="og:image:width" content="1200"/>
<meta property="og:image:height" content="630"/>
<meta name="twitter:title" content="TWITTER BANNER TITLE META TAG">
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<!-- Keywords for your paper to be indexed by-->
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<meta name="viewport" content="width=device-width, initial-scale=1">
<title>🦞 LBSTER 🦞 </title>
<link rel="icon" type="image/x-icon" href="static/images/favicon.ico">
<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro"
rel="stylesheet">
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href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
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</head>
<body>
<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column has-text-centered">
<h1 class="title is-1 publication-title">🦞 LBSTER 🦞</h1>
<div class="is-size-5 publication-authors">
<!-- Paper authors -->
<span class="author-block">
<a href="https://ncfrey.github.io" target="_blank">Frey Lab</a><sup>*</sup>,</span>
<!-- <span class="author-block">
<a href="SECOND AUTHOR PERSONAL LINK" target="_blank">Second Author</a><sup>*</sup>,</span>
<span class="author-block">
<a href="THIRD AUTHOR PERSONAL LINK" target="_blank">Third Author</a> -->
</span>
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<span class="author-block">Prescient Design<br>Genentech</span>
<!-- <span class="eql-cntrb"><small><br><sup>*</sup>Indicates Equal Contribution</small></span> -->
</div>
<div class="column has-text-centered">
<div class="publication-links">
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<span class="link-block">
<a href="https://arxiv.org/abs/2411.06090" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fas fa-file-pdf"></i>
</span>
<span>Concept Bottleneck Paper</span>
</a>
</span>
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<a href="static/pdfs/supplementary_material.pdf" target="_blank"
class="external-link button is-normal is-rounded is-dark">
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</span>
<span>Supplementary</span>
</a>
</span> -->
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<a href="https://github.com/prescient-design/lobster" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
</span>
<span>Code</span>
</a>
</span>
<!-- ArXiv abstract Link -->
<span class="link-block">
<a href="https://www.biorxiv.org/content/10.1101/2024.05.14.594108v1" target="_blank"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="ai ai-arxiv"></i>
</span>
<span>Cramming Paper</span>
</a>
</span>
</div>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Teaser video-->
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<video poster="" id="tree" autoplay controls muted loop height="100%">
Your video here
<source src="static/videos/banner_video.mp4"
type="video/mp4">
</video>
<h2 class="subtitle has-text-centered">
Aliquam vitae elit ullamcorper tellus egestas pellentesque. Ut lacus tellus, maximus vel lectus at, placerat pretium mi. Maecenas dignissim tincidunt vestibulum. Sed consequat hendrerit nisl ut maximus.
</h2>
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</div> -->
<!-- </section> -->
<!-- End teaser video -->
<!-- Paper abstract -->
<section class="section hero is-light">
<div class="container is-max-desktop">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
Protein language models (pLMs) are ubiquitous across biological machine learning research, but state-of-the-art models like ESM2 take hundreds of thousands of GPU hours to pre-train on the vast protein universe.
Resource requirements for scaling up pLMs prevent fundamental investigations into how optimal modeling choices might differ from those used in natural language. Here, we define a “cramming” challenge for pLMs and train
performant models in 24 hours on a single GPU. By re-examining many aspects of pLM training, we are able to train a 67 million parameter model in a single day that achieves comparable performance on downstream protein fitness
landscape inference tasks to ESM-3B, a model trained for over 15,000× more GPU hours than ours. We open source our library for training and inference,
LBSTER: Language models for Biological Sequence Transformation and Evolutionary Representation.
</p>
</div>
</div>
</div>
</div>
</section>
<!-- End paper abstract -->
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<div class="item">
<!-- Your image here -->
<img src="static/images/carousel1.jpg" alt="MY ALT TEXT"/>
<h2 class="subtitle has-text-centered">
Protein Language model cramming setup.
</h2>
</div>
<div class="item">
<!-- Your image here -->
<img src="static/images/carousel2.jpg" alt="MY ALT TEXT"/>
<h2 class="subtitle has-text-centered">
LBSTER: Language models for Biological Sequence Transformation and Evolutionary Representation
</h2>
</div>
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<!-- Your image here -->
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<!-- Youtube video -->
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<!-- Paper video. -->
<!-- <h2 class="title is-3">Video Presentation</h2>
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type="video/mp4">
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type="video/mp4">
</video>
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</section> -->
<!-- End video carousel -->
<!-- Paper poster -->
<section class="hero is-small is-light">
<div class="hero-body">
<div class="container">
<h2 class="title">Poster</h2>
<iframe src="static/pdfs/Cramming_MLSB_Neurips_2023_poster.pdf" width="100%" height="550">
</iframe>
</div>
</div>
</section>
<!--End paper poster -->
<!--BibTex citation -->
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@article{Frey2024.05.14.594108,
author = {Frey, Nathan C. and Joren, Taylor and Ismail, Aya Abdelsalam and Goodman, Allen and Bonneau, Richard and Cho, Kyunghyun and Gligorijevi{\'c}, Vladimir},
title = {Cramming Protein Language Model Training in 24 GPU Hours},
elocation-id = {2024.05.14.594108},
year = {2024},
doi = {10.1101/2024.05.14.594108},
publisher = {Cold Spring Harbor Laboratory},
URL = {https://www.biorxiv.org/content/early/2024/05/15/2024.05.14.594108},
eprint = {https://www.biorxiv.org/content/early/2024/05/15/2024.05.14.594108.full.pdf},
journal = {bioRxiv}
}</code></pre>
</div>
</section>
<!--End BibTex citation -->
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